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Direct comparison of MS ‐based label‐free and SILAC quantitative proteome profiling strategies in primary retinal M üller cells
To better understand the involvement of retinal Müller glial (RMG) cells in retinal diseases, we phenotyped primary porcine RMGs in dependence of cultivation time using different quantitative proteomic strategies. A well‐established LC‐MS/MS‐based quantification method was employed: stable isotope l...
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Published in: | Proteomics (Weinheim) 2012-06, Vol.12 (12), p.1902-1911 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | To better understand the involvement of retinal Müller glial (RMG) cells in retinal diseases, we phenotyped primary porcine RMGs in dependence of cultivation time using different quantitative proteomic strategies. A well‐established LC‐MS/MS‐based quantification method was employed: stable isotope labeling by amino acids in cell culture (SILAC) and directly compared to label‐free (LF) quantifications, based on total peak intensities using two different programs (MaxQuant and Progenesis LC‐MS). The overall numbers of detected proteins were largely similar (overlap of 1324 proteins), only a total of 173 proteins were significantly altered between the different culture conditions. However, among these, only 21 proteins were shared between the three analytical strategies. Hence, the majority of altered proteins only reached significance thresholds in one of the applied analyses with a larger overlap between the two LF approaches. Among the shared, differentially abundant proteins were known RMG markers as well as new proteins associated with glial cell transition. However, proteins correlated to cellular transitions and dedifferentiation were also found among the proteins only significant in one or two of the applied strategies. Consequently, the application of different quantification and analytical strategies could increase the analytical depths of proteomic phenotyping. |
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ISSN: | 1615-9853 1615-9861 |
DOI: | 10.1002/pmic.201100549 |